{"title":"Discover social relations and activities from ancient Chinese history book Zuo Zhuan","authors":"Bin Li, Lu Wang, Y. Wen, Xiaohe Chen, Yanhui Gu","doi":"10.1109/BESC.2017.8256367","DOIUrl":null,"url":null,"abstract":"The Chinese historical classics Zuo Zhuan is of great value to study the history between 722–468 BC. The persons in the literature and the places they have been to are typical topics in the studies of historical persons and events. However, the traditional full text retrieval is not sufficient for such studies, because either a person or a place usually has different names, and a name may refer to different entities. In this paper, we introduce our work on creating a database annotating each person and place with a unique ID. In addition, each place is tagged the name of today and the Geographic Information in Baidu Map. The database supplies full text, person and place multi-retrieval as well as social relations and events data. The personal travelling distances in Zuo Zhuan are also calculated.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BESC.2017.8256367","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The Chinese historical classics Zuo Zhuan is of great value to study the history between 722–468 BC. The persons in the literature and the places they have been to are typical topics in the studies of historical persons and events. However, the traditional full text retrieval is not sufficient for such studies, because either a person or a place usually has different names, and a name may refer to different entities. In this paper, we introduce our work on creating a database annotating each person and place with a unique ID. In addition, each place is tagged the name of today and the Geographic Information in Baidu Map. The database supplies full text, person and place multi-retrieval as well as social relations and events data. The personal travelling distances in Zuo Zhuan are also calculated.
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